This research was designed to investigate the factors affecting the frequency of use of ride-hailing in a fast-growing metropolitan region in Southeast Asia, Kuala Lumpur. An intercept survey was used to conduct this study in three potential locations that were acknowledged by one of the most famous ride-hailing companies in Kuala Lumpur. This study used non-parametric and machine learning techniques to analyze the data, including the Pearson chi-square test and Bayesian Network. From 38 statements (input variables), the Pearson chi-square test identified 14 variables as the most important. These variables were used as predictors in developing a BN model that predicts the probability of weekly usage frequency of ride-hai

    In this research, aflatoxins were produced, extracted, isolated, and purified in order to optimize the storage conditions of feed. Using a preparative thin layer chromatography (TLC) method, with commercially available plates of 1.5 to 2.0 mm, B1 aflatoxin was isolated from the feed samples of whole wheat, maize, and crushed rice, and the procedure was repeated four times. A purity value of 99 % for B1 aflatoxin was achieved and tested using spectrophotometric and chromatographic methods. As solvents, acetone:water (85:15l) was used for aflatoxin extraction from the feed sample, whereas methanol: water (50: 50) was used for trichothecenes extraction. The primary findings of this research indicate that B1 aflatoxin reac

Realizing the full potential of wireless sensor networks (WSNs) highlights many design issues, particularly the trade-offs concerning multiple conflicting improvements such as maximizing the route overlapping for efficient data aggregation and minimizing the total link cost. While the issues of data aggregation routing protocols and link cost function in a WSNs have been comprehensively considered in the literature, a trade-off improvement between these two has not yet been addressed. In this paper, a comprehensive weight for trade-off between different objectives has been employed, the so-called weighted data aggregation routing strategy (WDARS) which aims to maximize the overlap routes for efficient data aggregation and link cost

Recently, increasing material prices coupled with more acute environmental awareness and the implementation of regulation has driven a strong movement toward the adoption of sustainable construction technology. In the pavement industry, using low temperature asphalt mixes and recycled concrete aggregate are viewed as effective engineering solutions to address the challenges posed by climate change and sustainable development. However, to date, no research has investigated these two factors simultaneously for pavement material. This paper reports on initial work which attempts to address this shortcoming. At first, a novel treatment method is used to improve the quality of recycled concrete coarse aggregates. Thereafter, the treated recycled

Sheikh Hanafi was born in one of the popular shops of Baghdad with interlocking social relations, and had a profound impact this camp where his talents in the first Venco loving to Mahalah and Baghdad and was born with this development since his days looked forward to the folklore and folk. In the middle of his youth, including authoring loves the heritage of folk legacies began in motion, from Baghdad, books, articles, research has brought him wide acclaim were not possible without the seriousness and diligence, independence and self-Asamath that mushroom on them
The trip was one of his tools in the scientific fame has gone to many Eastern and Asian countries and visited religious and literary institutes and delivered the lectures an

       This paper uses Artificial Intelligence (AI) based algorithm analysis to classify breast cancer Deoxyribonucleic (DNA). Main idea is to focus on application of machine and deep learning techniques. Furthermore, a genetic algorithm is used to diagnose gene expression to reduce the number of misclassified cancers. After patients' genetic data are entered, processing operations that require filling the missing values using different techniques are used. The best data for the classification process are chosen by combining each technique using the genetic algorithm and comparing them  in terms of accuracy.

In this paper, we investigate some methods to solve one of the multi-criteria machine scheduling problems. The discussed problem is the total completion time and the total earliness jobs  To solve this problem, some heuristic methods are proposed which provided good results. The Branch and Bound (BAB) method is applied with new suggested upper and lower bounds to solve the discussed problem, which produced exact results for  in a reasonable time.